In distributed systems, different nodes of the distributed system (e.g., computer systems in a network) may operate in connection with the same set of data. Such nodes may operate relatively independently and, generally, the operation of a node can cause changes to data used by other nodes. In distributed systems, numerous issues can arise, such as node failure, erroneous operation, simultaneous or near simultaneous changes to data made by different nodes, and the like. Consensus protocols allow for data consistency in such distributed systems to protect and/or mitigate against such issues. While consensus protocols provide significant advantages for distributed systems, their use can have adverse effects. For instance, errors in data (often referred to as “poison pills”) may, by implementation of a consensus protocol, propagate throughout a distributed system. While the data may be valid from the point of view of a consensus protocol, the data may be invalid from the perspective of an application that utilizes the data. Depending on the nature of such data, such propagation of erroneous data can have adverse effects, such as by rendering a distributed system unreliable and, in some cases, inoperable.